Post-Covid air transport recovery: A multidimensional analysis of European airports under eurocontrol

Abstract

The study investigates the airlines in European countries that are operated by EuroControl according to key metrics such as departure punctuality, arrival punctuality, and operated schedules by using ARIMA, MDS, and PCA models. The research covers 2020–2024 with forecasts until June 2025, highlighting recovery trends, operational challenges, and model performance metrics. The findings provide insights for enhancing aviation resilience post-COVID-19, using advanced statistical techniques like Autoregressive Integrated Moving Average (ARIMA) models, Multidimensional Scaling (MDS) and Principal Component Analysis (PCA). The study identifies trends and patterns in recovery across different airports and states for forecasting and dimensional reduction by using MSE (Mean Squared Error), RMSE (Root Mean Squared Error), MAE (Mean Absolute Error) and R2 (Coefficient of Determination). The findings reveal a gradual recovery in flight operations with airports and states showing varied performance levels according to regions. The study underscores the importance of resilience and adaptability in the aviation industry, particularly in face of unforeseen crises like pandemics. The managerial implications provide valuable insights for policymakers and industry stakeholders aiming to improve airport operations and mitigate delays. Future recommendations include economic and operational indicators to enhance the forecasting models and further exploring digital transformation opportunities, increasing the aviation industry's resilience. © 2025 Elsevier B.V., All rights reserved.